Walkthrough all Matlab Code Used In This Project

Tabelle 12: Storing input data

Name	Application	Description
storingcropsteeringandframesoncsvrgb.m	Storing steering values and recorded frames	Steering values are stored in a CSV file as well as their corresponding frames.
storingcropsteeringandframesoncsvrgb_calibrated.m	Storing steering values and calibrated recorded frames in RGB.	Steering values are stored in a CSV file as well as their corresponding calibrated frames in RGB.
storingcropsteeringandframesoncsvrgb_calibrated.m		Pretrained NN to label each pixel in an image.
storingcropsteeringandframesoncsvrgb_calibrated.m		Pretrained NN to label each pixel in an image.
storingcropsteeringandframesoncsvrgb_calibrated.m		Pretrained NN to label each pixel in an image.
storingcropsteeringandframesoncsvrgb_calibrated.m		Pretrained NN to label each pixel in an image.
storingcropsteeringandframesoncsvrgb_calibrated.m		Pretrained NN to label each pixel in an image.
storingcropsteeringandframesoncsvrgb_calibrated.m		Pretrained NN to label each pixel in an image.
storingcropsteeringandframesoncsvrgb_calibrated.m		Pretrained NN to label each pixel in an image.

Tabelle 8: Calibration

Name	Application	Description
Calibrationchecker.m	ResNet-50/101	Pretrained NN for image classification tasks.
Calibrationchecker_video.m		Pretrained models for detecting and localizing objects.
test_camera_calibration.m		Pretrained NN to label each pixel in an image.
256by256frames.m		Pretrained NN to label each pixel in an image.
cali.m		Pretrained NN to label each pixel in an image.
calibration_256_256_script.m		Pretrained NN to label each pixel in an image.
calibration_500by220.m		Pretrained NN to label each pixel in an image.
calibration_500by220_final.m		Pretrained NN to label each pixel in an image.
calibration_with_one_image.m		Pretrained NN to label each pixel in an image.
test_extractedframes_256by256_calibrationpara.m		Pretrained NN to label each pixel in an image.

Tabelle 8: Lane Trackin

Name	Application	Description
Load	ResNet-50/101	Pretrained NN for image classification tasks.
Retrain		Pretrained models for detecting and localizing objects.
Finetune		Pretrained NN to label each pixel in an image.

Tabelle 8: python libraries

Name	Application	Description
Load	ResNet-50/101	Pretrained NN for image classification tasks.
Retrain		Pretrained models for detecting and localizing objects.
Finetune		Pretrained NN to label each pixel in an image.

Tabelle 8: autonomous driving

Name	Application	Description
Load	ResNet-50/101	Pretrained NN for image classification tasks.
Retrain		Pretrained models for detecting and localizing objects.
Finetune		Pretrained NN to label each pixel in an image.

Tabelle 8: Models

Name	Application	Description
Load	ResNet-50/101	Pretrained NN for image classification tasks.
Retrain		Pretrained models for detecting and localizing objects.
Finetune		Pretrained NN to label each pixel in an image.

Tabelle 8: Training

Name	Application	Description
Load	ResNet-50/101	Pretrained NN for image classification tasks.
Retrain		Pretrained models for detecting and localizing objects.
Finetune		Pretrained NN to label each pixel in an image.

Tabelle 8: .MAT files

Name	Application	Description
cameraParams.mat	ResNet-50/101	Pretrained NN for image classification tasks.
cameraCalibrationParams.mat		Pretrained models for detecting and localizing objects.
Finetune		Pretrained NN to label each pixel in an image.